knowledge representation


Also found in: Acronyms, Wikipedia.

knowledge representation

The subfield of artificial intelligence concerned with designing and using systems for storing knowledge - facts and rules about some subject.

A body of formally represented knowledge is based on a conceptualisation - an abstract view of the world that we wish to represent. In order to manipulate this knowledge we must specify how the abstract conceptualisation is represented as a concrete data structure. An ontology is an explicit specification of a conceptualisation.

knowledge representation

A method used to code knowledge in an expert system, typically a series of IF-THEN rules (IF this condition occurs, THEN take this action).
References in periodicals archive ?
His research interests include efficient reasoning procedures, planning, knowledge representation, and connections between computer science and statistical physics.
McIlraith, University of Toronto For significant contributions to knowledge representation, reasoning about action, and the formal foundations of the semantic web and diagnostic problem solving.
The conference series seeks insight from human argument to help solve research problems in the knowledge representation and reasoning dimensions of artificial intelligence.
Topics addressed include a methodology for the derivation and organization of knowledge for real-time control systems, behavior generation, world modeling and knowledge representation, sensory processing, temporal registration of sensed range images for autonomous navigation, advanced laser detection and ranging for driving unmanned ground vehicles, standards-based architectural framework for intelligent autonomous vehicles, performance evaluation of autonomous mobile robots, and the development of the Department of Defense's autonomous robotic ground vehicles.
Their overall themes are the contextual analysis and application domain, methodologies for knowledge representation and reasoning, information modeling, and enabling technologies and information processing paradigms.
Topics include but are not limited to the following: agent-based and multi-agent systems, cognitive modeling and human interaction, commonsense reasoning, computer vision, constraint satisfaction, search, and optimization, evolutionary computation, game playing and interactive entertainment, information retrieval, integration, and extraction, knowledge acquisition and ontologies, knowledge representation and reasoning, machine learning and data mining, model-based systems, multidisciplinary ai, natural language processing, planning and scheduling, probabilistic reasoning, robotics, web and information systems.
Drawing on concepts from psychology, human factors, knowledge representation, artificial intelligence, mathematical logic, and signal processing, they provide an explanation of data and information fusion for command and control systems.
The largest areas of submission were knowledge representation, multi-agent systems, and machine learning.
For significant contributions to knowledge representation and reasoning, planning, robotics, and services to the international AI community.
Some 350 contributions are organized into sections of keynote speeches, papers, posters, and demonstrations on consumer informatics, decision support systems, education for consumers and healthcare professionals, educational technologies and methodologies, electronic health record, ethical and legal issues, financial and administrative issues, Internet and communication, knowledge management, knowledge representation, nursing and health standards, open source software, organization impacts and changes, tele-health, ubiquitous computing, vocabulary, clinical informatics, confidentiality and security issues.

Full browser ?